Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples

Genetic Pathogenesis of Hypertrophic and Dilated Cardiomyopathy

Sarcomere cardiomyopathies are genetic diseases that perturb contractile function and lead to hypertrophic or dilated myocardial remodeling. Identification of preclinical mutation carriers has yielded insights into the earliest biomechanical defects that link pathogenic variants to cardiac dysfunction. Understanding this early molecular pathophysiology can illuminate modifiable pathways to reduce the emergence of overt cardiomyopathy and curb adverse outcomes. Here, the authors review current understandings of how human hypertrophic cardiomyopathy- and hypertrophic dilated cardiomyopathy-linked mutations disrupt the normal structure and function of the sarcomere.

Genetic Evaluation of Cardiomyopathy-A Heart Failure Society of America Practice Guideline

This guideline describes the approach and expertise needed for the genetic evaluation of cardiomyopathy. First published in 2009 by the Heart Failure Society of America (HFSA), the guideline has now been updated in collaboration with the American College of Medical Genetics and Genomics (ACMG). The writing group, composed of cardiologists and genetics professionals with expertise in adult and pediatric cardiomyopathy, reflects the emergence and increased clinical activity devoted to cardiovascular genetic medicine. The genetic evaluation of cardiomyopathy is a rapidly emerging key clinical priority, because high-throughput sequencing is now feasible for clinical testing and conventional interventions can improve survival, reduce morbidity, and enhance quality of life. Moreover, specific interventions may be guided by genetic analysis. A systematic approach is recommended: always a comprehensive family history; an expert phenotypic evaluation of the proband and at-risk family members to confirm a diagnosis and guide genetic test selection and interpretation; referral to expert centers as needed; genetic testing, with pre- and post-test genetic counseling; and specific guidance as indicated for drug and device therapies. The evaluation of infants and children demands special expertise. The approach to managing secondary and incidental sequence findings as recommended by the ACMG is provided.

Biomedical informatics and machine learning for clinical genomics

While tens of thousands of pathogenic variants are used to inform the many clinical applications of genomics, there remains limited information on quantitative disease risk for the majority of variants used in clinical practice. At the same time, rising demand for genetic counselling has prompted a growing need for computational approaches that can help interpret genetic variation. Such tasks include predicting variant pathogenicity and identifying variants that are too common to be penetrant. To address these challenges, researchers are increasingly turning to integrative informatics approaches. These approaches often leverage vast sources of data, including electronic health records and population-level allele frequency databases (e.g. gnomAD), as well as machine learning techniques such as support vector machines and deep learning. In this review, we highlight recent informatics and machine learning approaches that are improving our understanding of pathogenic variation and discuss obstacles that may limit their emerging role in clinical genomics.

High-depth whole genome sequencing of an Ashkenazi Jewish reference panel: enhancing sensitivity, accuracy, and imputation

While increasingly large reference panels for genome-wide imputation have been recently made available, the degree to which imputation accuracy can be enhanced by population-specific reference panels remains an open question. Here, we sequenced at full-depth (≥ 30×), across two platforms (Illumina X Ten and Complete Genomics, Inc.), a moderately large (n = 738) cohort of samples drawn from the Ashkenazi Jewish population. We developed a series of quality control steps to optimize sensitivity, specificity, and comprehensiveness of variant calls in the reference panel, and then tested the accuracy of imputation against target cohorts drawn from the same population. Quality control (QC) thresholds for the Illumina X Ten platform were identified that permitted highly accurate calling of single nucleotide variants across 94% of the genome. QC procedures also identified numerous regions that are poorly mapped using current reference or alternate assemblies. After stringent QC, the population-specific reference panel produced more accurate and comprehensive imputation results relative to publicly available, large cosmopolitan reference panels, especially in the range of rare variants that may be most critical to further progress in mapping of complex phenotypes. The population-specific reference panel also permitted enhanced filtering of clinically irrelevant variants from personal genomes.

Assessment of DNA repair susceptibility genes identified by whole exome sequencing in head and neck cancer

Head and neck cancer (HNC), the sixth most common cancer globally, stands second in India. In Northeast (NE) India, it is the sixth most common cause of death in males and seventh in females. Prolonged tobacco and alcohol consumption constitute the major etiological factors for HNC development, which induce DNA damage. Therefore, DNA repair pathway is a crucial system in maintaining genomic integrity and preventing carcinogenesis. The present work was aimed to predict the consequence of significant germline variants of the DNA repair genes in disease predisposition. Whole exome sequencing was performed in Ion Proton™ platform on 15 case-control samples from the HNC-prevalent states of Manipur, Mizoram, and Nagaland. Variant annotation was done in Ion Reporter™ as well as wANNOVAR. Subsequent statistical and bioinformatics analysis identified significant exonic and intronic variants associated with HNC. Amongst our observed variants, 78.6% occurred in ExAC, 94% reported in dbSNP and 5.8% & 9.3% variants were present in ClinVar and HGMD, respectively. The total variants were dispersed among 199 genes with DSBR and FA pathway being the most mutated pathways. The allelic association test suggested that the intronic variants in HLTF and RAD52 gene significantly associated (P < 0.05) with the risk (OR > 5), while intronic variants in PARP4, RECQL5, EXO1 and PER1 genes and exonic variant in TDP2 gene showed protection (OR < 1) for HNC. MDR analysis proposed the exonic variants in MSH6, BRCA2, PALB2 and TP53 genes and intronic variant in RECQL5 genetic region working together during certain phase of DNA repair mechanism for HNC causation. In addition, other intronic and 3'UTR variations caused modifications in the transcription factor binding sites and miRNA target sites associated with HNC. Large-scale validation in NE Indian population, in-depth structure prediction and subsequent simulation of our recognized polymorphisms is necessary to identify true causal variants related to HNC.

Classifying Cardiac Actin Mutations Associated With Hypertrophic Cardiomyopathy

Mutations in the cardiac actin gene (ACTC1) are associated with the development of hypertrophic cardiomyopathy (HCM). To date, 12 different ACTC1 mutations have been discovered in patients with HCM. Given the high degree of sequence conservation of actin proteins and the range of protein–protein interactions actin participates in, mutations in cardiac actin leading to HCM are particularly interesting. Here, we suggest the classification of ACTC1 mutations based on the location of the resulting amino acid change in actin into three main groups: (1) those affecting only the binding site of the myosin molecular motor, termed M-class mutations, (2) those affecting only the binding site of the tropomyosin (Tm) regulatory protein, designated T-class mutations, and (3) those affecting both the myosin- and Tm-binding sites, called MT-class mutations. To understand the precise pathogenesis of cardiac actin mutations and develop treatments specific to the molecular cause of disease, we need to integrate rapidly growing structural information with studies of regulated actomyosin systems.

Insights Into Hypertrophic Cardiomyopathy Evaluation Through Follow-up of a Founder Pathogenic Variant

INTRODUCTION AND OBJECTIVES

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease. The current challenge relies on the accurate classification of the pathogenicity of the variants. Transthoracic echocardiography (TTE) is recommended at initial evaluation and cardiac magnetic resonance (CMR) imaging should also be considered. We aimed to reappraise the penetrance and clinical expression of the MYBPC3 p.G263* variant.

METHODS

Three hundred and eighty-four HCM probands and a control cohort of 450 individuals were studied for the main sarcomere genes by next-generation sequencing. All MYBPC3 p.G263* carriers were identified and family screening was performed. Clinical information was recorded retrospectively before 2015 and prospectively thereafter. Extra effort was invested in performing CMR in all carriers, despite TTE results.

RESULTS

Thirteen HCM probands and none of the controls were carriers of the MYBPC3 p.G263* pathogenic variant (according to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology). A total of 39 carriers were identified with family screening. Most patients with HCM were asymptomatic at the time of diagnosis and showed late-onset disease. Despite having a relatively benign course in the young, late HCM-related complications could occur. Penetrance was around 70% when evaluated by TTE and was 87.2% with TTE plus CMR. Penetrance was age-dependent, reaching 100% in carriers older than 55 years.

CONCLUSIONS

MYBPC3 p.G263* shares with most truncating pathogenic variants in this gene a late onset, relatively benign clinical course in the young, and high penetrance. Cardiac magnetic resonance could be a useful tool to evaluate carriers despite TTE results.

Pleiotropic Effects of Variants in Dementia Genes in Parkinson Disease

Background: The prevalence of dementia in Parkinson disease (PD) increases dramatically with advancing age, approaching 80% in patients who survive 20 years with the disease. Increasing evidence suggests clinical, pathological and genetic overlap between Alzheimer disease, dementia with Lewy bodies and frontotemporal dementia with PD. However, the contribution of the dementia-causing genes to PD risk, cognitive impairment and dementia in PD is not fully established. Objective: To assess the contribution of coding variants in Mendelian dementia-causing genes on the risk of developing PD and the effect on cognitive performance of PD patients. Methods: We analyzed the coding regions of the amyloid-beta precursor protein (APP), Presenilin 1 and 2 (PSEN1, PSEN2), and Granulin (GRN) genes from 1,374 PD cases and 973 controls using pooled-DNA targeted sequence, human exome-chip and whole-exome sequencing (WES) data by single variant and gene base (SKAT-O and burden tests) analyses. Global cognitive function was assessed using the Mini-Mental State Examination (MMSE) or the Montreal Cognitive Assessment (MoCA). The effect of coding variants in dementia-causing genes on cognitive performance was tested by multiple regression analysis adjusting for gender, disease duration, age at dementia assessment, study site and APOE carrier status. Results: Known AD pathogenic mutations in the PSEN1 (p.A79V) and PSEN2 (p.V148I) genes were found in 0.3% of all PD patients. There was a significant burden of rare, likely damaging variants in the GRN and PSEN1 genes in PD patients when compared with frequencies in the European population from the ExAC database. Multiple regression analysis revealed that PD patients carrying rare variants in the APP, PSEN1, PSEN2, and GRN genes exhibit lower cognitive tests scores than non-carrier PD patients (p = 2.0 × 10-4), independent of age at PD diagnosis, age at evaluation, APOE status or recruitment site. Conclusions: Pathogenic mutations in the Alzheimer disease-causing genes (PSEN1 and PSEN2) are found in sporadic PD patients. PD patients with cognitive decline carry rare variants in dementia-causing genes. Variants in genes causing Mendelian neurodegenerative diseases exhibit pleiotropic effects.

Identification of Misclassified ClinVar Variants via Disease Population Prevalence

There is a significant interest in the standardized classification of human genetic variants. We used whole-genome sequence data from 10,495 unrelated individuals to contrast population frequency of pathogenic variants to the expected population prevalence of the disease. Analyses included the ACMG-recommended 59 gene-condition sets for incidental findings and 463 genes associated with 265 OrphaNet conditions. A total of 25,505 variants were used to identify patterns of inflation (i.e., excess genetic risk and misclassification). Inflation increases as the level of evidence supporting the pathogenic nature of the variant decreases. We observed up to 11.5% of genetic disorders with inflation in pathogenic variant sets and up to 92.3% for the variant set with conflicting interpretations. This improved to 7.7% and 57.7%, respectively, after filtering for disease-specific allele frequency. The patterns of inflation were replicated using public data from more than 138,000 genomes. The burden of rare variants was a main contributing factor of the observed inflation, indicating collective misclassified rare variants. We also analyzed the dynamics of re-classification of variant pathogenicity in ClinVar over time, which indicates progressive improvement in variant classification. The study shows that databases include a significant proportion of wrongly ascertained variants; however, it underscores the critical role of ClinVar to contrast claims and foster validation across submitters.

Cardiovascular Precision Medicine in the Genomics Era

Precision medicine strives to delineate disease using multiple data sources-from genomics to digital health metrics-in order to be more precise and accurate in our diagnoses, definitions, and treatments of disease subtypes. By defining disease at a deeper level, we can treat patients based on an understanding of the molecular underpinnings of their presentations, rather than grouping patients into broad categories with one-size-fits-all treatments. In this review, the authors examine how precision medicine, specifically that surrounding genetic testing and genetic therapeutics, has begun to make strides in both common and rare cardiovascular diseases in the clinic and the laboratory, and how these advances are beginning to enable us to more effectively define risk, diagnose disease, and deliver therapeutics for each individual patient.

Molecular Defects in Cardiac Myofilament Ca2+-Regulation Due to Cardiomyopathy-Linked Mutations Can Be Reversed by Small Molecules Binding to Troponin

The inherited cardiomyopathies, hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) are relatively common, potentially life-threatening and currently untreatable. Mutations are often in the contractile proteins of cardiac muscle and cause abnormal Ca²⁺ regulation via troponin. HCM is usually linked to higher myofilament Ca²⁺-sensitivity whilst in both HCM and DCM mutant tissue there is often an uncoupling of the relationship between troponin I (TnI) phosphorylation by PKA and modulation of myofilament Ca²⁺-sensitivity, essential for normal responses to adrenaline. The adrenergic response is blunted, and this may predispose the heart to failure under stress. At present there are no compounds or interventions that can prevent or treat sarcomere cardiomyopathies. There is a need for novel therapies that act at a more fundamental level to affect the disease process. We demonstrated that epigallocatechin-3 gallate (EGCG) was found to be capable of restoring the coupled relationship between Ca²⁺-sensitivity and TnI phosphorylation in mutant thin filaments to normal in vitro, independent of the mutation (15 mutations tested). We have labeled this property "re-coupling." The action of EGCG in vitro to reverse the abnormality caused by myopathic mutations would appear to be an ideal pharmaceutical profile for treatment of inherited HCM and DCM but EGCG is known to be promiscuous in vivo and is thus unsuitable as a therapeutic drug. We therefore investigated whether other structurally related compounds can re-couple myofilaments without these off-target effects. We used the quantitative in vitro motility assay to screen 40 compounds, related to C-terminal Hsp90 inhibitors, and found 23 that can re-couple mutant myofilaments. There is no correlation between re-couplers and Hsp90 inhibitors. The Ca²⁺-sensitivity shift due to TnI phosphorylation was restored to 2.2 ± 0.01-fold (n = 19) compared to 2.0 ± 0.24-fold (n = 7) in wild-type thin filaments. Many of these compounds were either pure re-couplers or pure desensitizers, indicating these properties are independent; moreover, re-coupling ability could be lost with small changes of compound structure, indicating the possibility of specificity. Small molecules that can re-couple may have therapeutic potential. HIGHLIGHTS - Inherited cardiomyopathies are common diseases that are currently untreatable at a fundamental level and therefore finding a small molecule treatment is highly desirable.- We have identified a molecular level dysfunction common to nearly all mutations: uncoupling of the relationship between troponin I phosphorylation and modulation of myofilament Ca²⁺-sensitivity, essential for normal responses to adrenaline.- We have identified a new class of drugs that are capable of both reducing Ca²⁺-sensitivity and/or recouping the relationship between troponin I phosphorylation and Ca²⁺-sensitivity.- The re-coupling phenomenon can be explained on the basis of a single mechanism that is testable.- Measurements with a wide range of small molecules of varying structures can indicate the critical molecular features required for recoupling and allows the prediction of other potential re-couplers.

Short-term costs of integrating whole-genome sequencing into primary care and cardiology settings: a pilot randomized trial

Purpose

Great uncertainty exists about the costs associated with whole genome sequencing (WGS).

Methods

One hundred cardiology patients with cardiomyopathy diagnoses, and 100 ostensibly healthy primary care patients were randomized to receive a family history report alone or with a WGS report. Cardiology patients also reviewed prior genetic test results. WGS costs were estimated by tracking resource use and staff time. Downstream costs were estimated by identifying services in administrative data, medical records, and patient surveys for 6 months.

Results

The incremental cost per patient of WGS testing was $5,098 in cardiology settings and $5,073 in primary care settings compared to family history alone. Mean six month downstream costs did not differ statistically between the control and WGS arms in either setting (cardiology: difference = −$1,560, 95%CI −$7,558 to $3,866, p=0.36; primary care: difference = $681, 95%CI −$884 to $2,171, p=0.70). Scenario analyses showed the cost reduction of omitting or limiting the types of secondary findings was less than $69 and $182 per patient in cardiology and primary care, respectively.

Conclusion

Short-term costs of WGS were driven by the costs of sequencing and interpretation rather than downstream healthcare. Disclosing additional types of secondary findings has a limited cost impact following disclosure.

Statistical Validation of Rare Complement Variants Provides Insights into the Molecular Basis of Atypical Hemolytic Uremic Syndrome and C3 Glomerulopathy

Atypical hemolytic uremic syndrome (aHUS) and C3 glomerulopathy (C3G) are associated with dysregulation and overactivation of the complement alternative pathway. Typically, gene analysis for aHUS and C3G is undertaken in small patient numbers, yet it is unclear which genes most frequently predispose to aHUS or C3G. Accordingly, we performed a six-center analysis of 610 rare genetic variants in 13 mostly complement genes (CFH, CFI, CD46, C3, CFB, CFHR1, CFHR3, CFHR4, CFHR5, CFP, PLG, DGKE, and THBD) from >3500 patients with aHUS and C3G. We report 371 novel rare variants (RVs) for aHUS and 82 for C3G. Our new interactive Database of Complement Gene Variants was used to extract allele frequency data for these 13 genes using the Exome Aggregation Consortium server as the reference genome. For aHUS, significantly more protein-altering rare variation was found in five genes CFH, CFI, CD46, C3, and DGKE than in the Exome Aggregation Consortium (allele frequency < 0.01%), thus correlating these with aHUS. For C3G, an association was only found for RVs in C3 and the N-terminal C3b-binding or C-terminal nonsurface-associated regions of CFH In conclusion, the RV analyses showed nonrandom distributions over the affected proteins, and different distributions were observed between aHUS and C3G that clarify their phenotypes.

Systems analysis of dilated cardiomyopathy in the next generation sequencing era

Dilated cardiomyopathy (DCM) is a form of severe failure of cardiac muscle caused by a long list of etiologies ranging from myocardial infarction, DNA mutations in cardiac genes, to toxics. Systems analysis integrating next-generation sequencing (NGS)-based omics approaches, such as the sequencing of DNA, RNA, and chromatin, provide valuable insights into DCM mechanisms. The outcome and interpretation of NGS methods can be affected by the localization of cardiac biopsy, level of tissue degradation, and variable ratios of different cell populations, especially in the presence of fibrosis. Heart tissue composition may even differ between sexes, or siblings carrying the same disease causing mutation. Therefore, before planning any experiments, it is important to fully appreciate the complexities of DCM, and the selection of samples suitable for given research question should be an interdisciplinary effort involving clinicians and biologists. The list of NGS omics datasets in DCM to date is short. More studies have to be performed to contribute to public data repositories and facilitate systems analysis. In addition, proper data integration is a difficult task requiring complex computational approaches. Despite these complications, there are multiple promising implications of systems analysis in DCM. By combining various types of datasets, for example, RNA-seq, ChIP-seq, or 4C, deep insights into cardiac biology, and possible biomarkers and treatment targets, can be gained. Systems analysis can also facilitate the annotation of noncoding mutations in cardiac-specific DNA regulatory regions that play a substantial role in maintaining the tissue- and cell-specific transcriptional programs in the heart. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Laboratory Methods and Technologies > Genetic/Genomic Methods Laboratory Methods and Technologies > RNA Methods.

A literature review at genome scale: improving clinical variant assessment

PURPOSE

Over 150,000 variants have been reported to cause Mendelian disease in the medical literature. It is still difficult to leverage this knowledge base in clinical practice, as many reports lack strong statistical evidence or may include false associations. Clinical laboratories assess whether these variants (along with newly observed variants that are adjacent to these published ones) underlie clinical disorders.

METHODS

We investigated whether citation data-including journal impact factor and the number of cited variants (NCV) in each gene with published disease associations-can be used to improve variant assessment.

RESULTS

Surprisingly, we found that impact factor is not predictive of pathogenicity, but the NCV score for each gene can provide statistical support for prediction of pathogenicity. When this gene-level citation metric is combined with variant-level evolutionary conservation and structural features, classification accuracy reaches 89.5%. Further, variants identified in clinical exome sequencing cases have higher NCVs than do simulated rare variants from the Exome Aggregation Consortium database within the same set of genes and functional consequences (P < 2.22  ×  10^-16).

CONCLUSION

Aggregate citation data can complement existing variant-based predictive algorithms, and can boost their performance without the need to access and review large numbers of papers. The NCV is a slow-growing metric of scientific knowledge about each gene's association with disease.

CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation

PURPOSE

Internationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier ( http://www.cardioclassifier.org ), a semiautomated decision-support tool for inherited cardiac conditions (ICCs).

METHODS

CardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.

RESULTS

We benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher's P = 1.1  ×  10^-18), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.

CONCLUSION

CardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.

Multiple Gene Variants in Hypertrophic Cardiomyopathy in the Era of Next-Generation Sequencing

BACKGROUND

Multiple likely pathogenic/pathogenic (LP/P; ≥2) variants in patients with hypertrophic cardiomyopathy were described 10 years ago with a prevalence of 5%. We sought to re-examine the significance of multiple rare variants in patients with hypertrophic cardiomyopathy in the setting of comprehensive and targeted panels.

METHODS AND RESULTS

Of 758 hypertrophic cardiomyopathy probands, we included 382 with ≥45 cardiomyopathy genes screened. There were 224 (59%) with ≥1 rare variant (allele frequency ≤0.02%). Variants were analyzed using varying sized gene panels to represent comprehensive or targeted testing. Based on a 45-gene panel, 127 (33%) had a LP/P variant, 139 (36%) had variants of uncertain significance, and 66 (17%) had multiple rare variants. A targeted 8-gene panel yielded 125 (32%) LP/P variants, 52 (14%) variants of uncertain significance, and 14 (4%) had multiple rare variants. No proband had 2 LP/P variants. Including affected family members (total n=412), cluster-adjusted analyses identified a phenotype effect, with younger age (odds ratio, 0.95; 95% confidence interval, 0.92-0.98; P=0.004) and family history of sudden cardiac death (odds ratio, 3.5; 95% confidence interval, 1.3-9.9; P=0.02) significantly more likely in multiple versus single variant patients when considering an 8-gene panel but not larger panels. Those with multiple variants had worse event-free survival from all-cause death, cardiac transplantation, and cardiac arrest (log-rank P=0.008).

CONCLUSIONS

No proband had multiple LP/P variants in contrast to previous reports. However, multiple rare variants regardless of classification were seen in 4% and contributed to earlier disease onset and cardiac events. Our findings support a cumulative variant hypothesis in hypertrophic cardiomyopathy.

Novel Genetic Triggers and Genotype-Phenotype Correlations in Patients With Left Ventricular Noncompaction

BACKGROUND

Left ventricular noncompaction (LVNC) is a genetically and phenotypically heterogeneous disease and, although increasingly recognized in clinical practice, there is a lack of widely accepted diagnostic criteria. We sought to identify novel genetic causes of LVNC and describe genotype-phenotype correlations.

METHODS AND RESULTS

A total of 190 patients from 174 families with left ventricular hypertrabeculation (LVHT) or LVNC were referred for cardiac magnetic resonance and whole-exome sequencing. A total of 425 control individuals were included to identify variants of interest (VOIs). We found an excess of 138 VOIs in 102 (59%) unrelated patients in 54 previously identified LVNC or other known cardiomyopathy genes. VOIs were found in 68 of 90 probands with LVNC and 34 of 84 probands with LVHT (76% and 40%, respectively; P<0.001). We identified 0, 1, and ≥2 VOIs in 72, 74, and 28 probands, respectively. We found increasing number of VOIs in a patient strongly correlated with several markers of disease severity, including ratio of noncompacted to compacted myocardium (P<0.001) and left ventricular ejection fraction (P=0.01). The presence of sarcomeric gene mutations was associated with increased occurrence of late gadolinium enhancement (P=0.004).

CONCLUSIONS

LVHT and LVNC likely represent a continuum of genotypic disease with differences in severity and variable phenotype explained, in part, by the number of VOIs and whether mutations are present in sarcomeric or nonsarcomeric genes. Presence of VOIs is common in patients with LVHT. Our findings expand the current clinical and genetic diagnostic approaches for patients with LVHT and LVNC.

Adaptation and validation of the ACMG/AMP variant classification framework for MYH7-associated inherited cardiomyopathies: recommendations by ClinGen's Inherited Cardiomyopathy Expert Panel

Purpose

Integrating genomic sequencing in clinical care requires standardization of variant interpretation practices. The Clinical Genome Resource has established expert panels to adapt the American College of Medical Genetics and Genomics/Association for Molecular Pathology classification framework for specific genes and diseases. The Cardiomyopathy Expert Panel selected MYH7, a key contributor to inherited cardiomyopathies, as a pilot gene to develop a broadly applicable approach.

Methods

Expert revisions were tested with 60 variants using a structured double review by pairs of clinical and diagnostic laboratory experts. Final consensus rules were established via iterative discussions.

Results

Adjustments represented disease-/gene-informed specifications (12) or strength adjustments of existing rules (5). Nine rules were deemed not applicable. Key specifications included quantitative frameworks for minor allele frequency thresholds, the use of segregation data, and a semiquantitative approach to counting multiple independent variant occurrences where fully controlled case-control studies are lacking. Initial inter-expert classification concordance was 93%. Internal data from participating diagnostic laboratories changed the classification of 20% of the variants (n = 12), highlighting the critical importance of data sharing.

Conclusion

These adapted rules provide increased specificity for use in MYH7-associated disorders in combination with expert review and clinical judgment and serve as a stepping stone for genes and disorders with similar genetic and clinical characteristics.

Human γ2-AMPK Mutations

In humans, dominant mutations in the gene encoding the regulatory γ2-subunit of AMP-activated protein kinase (PRKAG2) result in a highly penetrant phenotype dominated by cardiac features: left ventricular hypertrophy, ventricular pre-excitation, atrial tachyarrhythmia, cardiac conduction disease, and myocardial glycogen storage. The discovery of a link between the cell's fundamental energy sensor, AMPK, and inherited cardiac disease catalyzed intense interest into the biological role of AMPK in the heart. In this chapter, we provide an introduction to the spectrum of human disease resulting from pathogenic variants in PRKAG2, outlining its discovery, clinical genetics, and current perspectives on its pathogenesis and highlighting mechanistic insights derived through the evaluation of disease models. We also present a clinical perspective on the major components of the cardiomyopathy associated with mutations in PRKAG2, together with less commonly described extracardiac features, its prognosis, and principles of management.

Role of titin in cardiomyopathy: from DNA variants to patient stratification

Dilated cardiomyopathy (DCM) affects approximately 1 in 250 individuals and is the leading indication for heart transplantation. DCM is often familial, and the most common genetic predisposition is a truncating variation in the giant sarcomeric protein, titin, which occurs in up to 15% of ambulant patients with DCM and 25% of end-stage or familial cases. In this article, we review the evidence for the role of titin truncation in the pathogenesis of DCM and our understanding of the molecular mechanisms and pathophysiological consequences of variation in the gene encoding titin (TTN). Such variation is common in the general population (up to 1% of individuals), and we consider key features that discriminate variants with disease-causing potential from those that are benign. We summarize strategies for clinical interpretation of genetic variants for use in the diagnosis of patients and the evaluation of their relatives. Finally, we consider the contemporary and potential future role for genetic stratification in cardiomyopathy and in the general population, evaluating titin variation as a predictor of outcome and treatment response for precision medicine.

Molecular genetics of syndromic and non-syndromic forms of parathyroid carcinoma

Parathyroid carcinoma (PC) may occur as part of a complex hereditary syndrome or an isolated (i.e., non-syndromic) non-hereditary (i.e., sporadic) endocrinopathy. Studies of hereditary and syndromic forms of PC, which include the hyperparathyroidism-jaw tumor syndrome (HPT-JT), multiple endocrine neoplasia types 1 and 2 (MEN1 and MEN2), and familial isolated primary hyperparathyroidism (FIHP), have revealed some genetic mechanisms underlying PC. Thus, cell division cycle 73 (CDC73) germline mutations cause HPT-JT, and CDC73 mutations occur in 70% of sporadic PC, but in only ∼2% of parathyroid adenomas. Moreover, CDC73 germline mutations occur in 20%-40% of patients with sporadic PC and may reveal unrecognized HPT-JT. This indicates that CDC73 mutations are major driver mutations in the etiology of PCs. However, there is no genotype-phenotype correlation and some CDC73 mutations (e.g., c.679_680insAG) have been reported in patients with sporadic PC, HPT-JT, or FIHP. Other genes involved in sporadic PC include germline MEN1 and rearranged during transfection (RET) mutations and somatic alterations of the retinoblastoma 1 (RB1) and tumor protein P53 (TP53) genes, as well as epigenetic modifications including DNA methylation and histone modifications, and microRNA misregulation. This review summarizes the genetics and epigenetics of the familial syndromic and non-syndromic (sporadic) forms of PC.

Novel genes associated with amyotrophic lateral sclerosis: diagnostic and clinical implications

BACKGROUND

The disease course of amyotrophic lateral sclerosis (ALS) is rapid and, because its pathophysiology is unclear, few effective treatments are available. Genetic research aims to understand the underlying mechanisms of ALS and identify potential therapeutic targets. The first gene associated with ALS was SOD1, identified in 1993 and, by early 2014, more than 20 genes had been identified as causative of, or highly associated with, ALS. These genetic discoveries have identified key disease pathways that are therapeutically testable and could potentially lead to the development of better treatments for people with ALS.

RECENT DEVELOPMENTS

Since 2014, seven additional genes have been associated with ALS (MATR3, CHCHD10, TBK1, TUBA4A, NEK1, C21orf2, and CCNF), all of which were identified by genome-wide association studies, whole genome studies, or exome sequencing technologies. Each of the seven novel genes code for proteins associated with one or more molecular pathways known to be involved in ALS. These pathways include dysfunction in global protein homoeostasis resulting from abnormal protein aggregation or a defect in the protein clearance pathway, mitochondrial dysfunction, altered RNA metabolism, impaired cytoskeletal integrity, altered axonal transport dynamics, and DNA damage accumulation due to defective DNA repair. Because these novel genes share common disease pathways with other genes implicated in ALS, therapeutics targeting these pathways could be useful for a broad group of patients stratified by genotype. However, the effects of these novel genes have not yet been investigated in animal models, which will be a key step to translating these findings into clinical practice. WHERE NEXT?: The identification of these seven novel genes has been important in unravelling the molecular mechanisms underlying ALS. However, our understanding of what causes ALS is not complete, and further genetic research will provide additional detail about its causes. Increased genetic knowledge will also identify potential therapeutic targets and could lead to the development of individualised medicine for patients with ALS. These developments will have a direct effect on clinical practice when genome sequencing becomes a routine and integral part of disease diagnosis and management.

Utility of Population-Level DNA Sequence Data in the Diagnosis of Hereditary Endocrine Disease

Context

Genetic testing is increasingly used for clinical diagnosis, although variant interpretation presents a major challenge because of high background rates of rare coding-region variation, which may contribute to inaccurate estimates of variant pathogenicity and disease penetrance.

Objective

To use the Exome Aggregation Consortium (ExAC) data set to determine the background population frequencies of rare germline coding-region variants in genes associated with hereditary endocrine disease and to evaluate the clinical utility of these data.

Design Setting Participants

Cumulative frequencies of rare nonsynonymous single-nucleotide variants were established for 38 endocrine disease genes in 60,706 unrelated control individuals. The utility of gene-level and variant-level metrics of tolerability was assessed, and the pathogenicity and penetrance of germline variants previously associated with endocrine disease evaluated.

Results

The frequency of rare coding-region variants differed markedly between genes and was correlated with the degree of evolutionary conservation. Genes associated with dominant monogenic endocrine disorders typically harbored fewer rare missense and/or loss-of-function variants than expected. In silico variant prediction tools demonstrated low clinical specificity. The frequency of several endocrine disease‒associated variants in the ExAC cohort far exceeded estimates of disease prevalence, indicating either misclassification or overestimation of disease penetrance. Finally, we illustrate how rare variant frequencies may be used to anticipate expected rates of background rare variation when performing disease-targeted genetic testing.

Conclusions

Quantifying the frequency and spectrum of rare variation using population-level sequence data facilitates improved estimates of variant pathogenicity and penetrance and should be incorporated into the clinical decision-making algorithm when undertaking genetic testing.

Development of a communication aid for explaining hypertrophic cardiomyopathy genetic test results

Background

Large gene panels are now commonplace for hypertrophic cardiomyopathy (HCM), increasing the yield of uncertain genetic findings. Few resources exist which aim to facilitate communication of HCM genetic test results. We sought to develop, pilot, and refine a communication aid for probands receiving HCM genetic test results.

Methods

Development was a multi-step process involving expertise of a multidisciplinary team, literature review, and empirical experience. The aid went through an iterative revision process throughout the piloting phase to incorporate feedback. HCM probands attending a specialized multidisciplinary HCM clinic, aged ≥ 18 years and genetic test results available for disclosure between May and August 2016, or recently received their gene results (January–April 2015) were eligible. A purposive sampling strategy was employed, recruiting those attending clinic during the study period or those who could attend without difficulty.

Results

We developed and pilot tested a genetic counsellor-led communication aid. Based on clinical expertise, the aid addresses (a) what genetic testing is, (b) implications for the patient, (c) reasoning for variant classification, and (d) implications for the family. Pilot data were sought to assess knowledge, feasibility, and acceptability using a self-report survey 2 weeks post-intervention. Twelve of 13 participants completed the follow-up questionnaire. Participants valued the individualised nature of the aid, recommended use of the aid, and indicated genetic knowledge, and family communication was better facilitated. Iterative modification of images helped to more simply depict important genetic concepts.

Conclusions

We have developed a tool that is feasible, acceptable, and helpful to patients receiving genetic results. This is an important first step, and trial of the aid to assess effectiveness compared to usual care will follow.

Molecular Autopsy for Sudden Death in the Young: Is Data Aggregation the Key?

The Scripps molecular autopsy study seeks to incorporate genetic testing into the postmortem examination of cases of sudden death in the young (<45 years old). Here, we describe the results from the first 2 years of the study, which consisted of whole exome sequencing (WES) of a cohort of 50 cases predominantly from San Diego County. Apart from the individual description of cases, we analyzed the data at the cohort-level, which brought new perspectives on the genetic causes of sudden death. We investigated the advantages and disadvantages of using WES compared to a gene panel for cardiac disease (usually the first genetic test used by medical examiners). In an attempt to connect complex clinical phenotypes with genotypes, we classified samples by their genetic fingerprint. Finally, we studied the benefits of analyzing the mitochondrial DNA genome. In this regard, we found that half of the cases clinically diagnosed as sudden infant death syndrome had an increased ratio of heteroplasmic variants, and that the variants were also present in the mothers. We believe that community-based data aggregation and sharing will eventually lead to an improved classification of variants. Allele frequencies for the all cases can be accessed via our genomics browser at https://genomics.scripps.edu/browser.

When signalling goes wrong: pathogenic variants in structural and signalling proteins causing cardiomyopathies

Cardiomyopathies are a diverse group of cardiac disorders with distinct phenotypes, depending on the proteins and pathways affected. A substantial proportion of cardiomyopathies are inherited and those will be the focus of this review article. With the wide application of high-throughput sequencing in the practice of clinical genetics, the roles of novel genes in cardiomyopathies are recognised. Here, we focus on a subgroup of cardiomyopathy genes [TTN, FHL1, CSRP3, FLNC and PLN, coding for Titin, Four and a Half LIM domain 1, Muscle LIM Protein, Filamin C and Phospholamban, respectively], which, despite their diverse biological functions, all have important signalling functions in the heart, suggesting that disturbances in signalling networks can contribute to cardiomyopathies.

Analysis of neurodegenerative Mendelian genes in clinically diagnosed Alzheimer Disease

Alzheimer disease (AD), Frontotemporal lobar degeneration (FTD), Amyotrophic lateral sclerosis (ALS) and Parkinson disease (PD) have a certain degree of clinical, pathological and molecular overlap. Previous studies indicate that causative mutations in AD and FTD/ALS genes can be found in clinical familial AD. We examined the presence of causative and low frequency coding variants in the AD, FTD, ALS and PD Mendelian genes, in over 450 families with clinical history of AD and over 11,710 sporadic cases and cognitive normal participants from North America. Known pathogenic mutations were found in 1.05% of the sporadic cases, in 0.69% of the cognitively normal participants and in 4.22% of the families. A trend towards enrichment, albeit non-significant, was observed for most AD, FTD and PD genes. Only PSEN1 and PINK1 showed consistent association with AD cases when we used ExAC as the control population. These results suggest that current study designs may contain heterogeneity and contamination of the control population, and that current statistical methods for the discovery of novel genes with real pathogenic variants in complex late onset diseases may be inadequate or underpowered to identify genes carrying pathogenic mutations.

Re-evaluating pathogenicity of variants associated with the long QT syndrome

INTRODUCTION

Genetic testing for congenital long QT syndrome (LQTS) has become common. Recent studies have shown that some variants labelled as pathogenic might be misclassified due to sparse case reports and relatively common allele frequencies (AF) in the general population. This study aims to evaluate the presence of LQTS-associated variants in the Genome Aggregation Database (gnomAD) population, and assess the functional impact of these variants.

METHODS AND RESULTS

Variants associated with LQTS from the Human Gene Mutation Database were extracted and matched to the gnomAD to evaluate population-based AF. We used MetaSVM to predict the function of LQTS variants. Allele distribution by protein topology in KCNQ1, KCNH2, and SCN5A was compared between gnomAD (n = 123,136) and a cohort of LQTS patients aggregated from eight published studies (n = 2,683). Among the 1,415 LQTS-associated single nucleotide variants in 30 genes, 347 (25%) are present in gnomAD; 24% of the 347 variants were predicted as functionally tolerated compared with 4% of variants not present in gnomAD (P < 0.001). Of the 347 pathogenic variants in gnomAD, seven (2%) had an AF of ≥ 0.001 and 65 (19%) variants had an AF of ≥ 0.0001. In KCNQ1, KCNH2, and SCN5A, allele distribution by protein functional region was significantly different with gnomAD alleles appearing less frequently in highly pathogenic domains than case alleles.

CONCLUSION

A significant number of LQTS variants have insufficient evidence for pathogenicity and relatively common AF in the general population. Caution should be used when ascribing pathogenicity to these variants.

Prenatal exome sequencing in anomalous fetuses: new opportunities and challenges

PurposeWe investigated the diagnostic and clinical performance of exome sequencing in fetuses with sonographic abnormalities with normal karyotype and microarray and, in some cases, normal gene-specific sequencing.MethodsExome sequencing was performed on DNA from 15 anomalous fetuses and from the peripheral blood of their parents. Parents provided consent to be informed of diagnostic results in the fetus, medically actionable findings in the parents, and their identification as carrier couples for significant autosomal recessive conditions. We assessed the perceptions and understanding of exome sequencing using mixed methods in 15 mother-father dyads.ResultsIn seven (47%) of 15 fetuses, exome sequencing provided a diagnosis or possible diagnosis with identification of variants in the following genes: COL1A1, MUSK, KCTD1, RTTN, TMEM67, PIEZO1 and DYNC2H1. One additional case revealed a de novo nonsense mutation in a novel candidate gene (MAP4K4). The perceived likelihood that exome sequencing would explain the results (5.2 on a 10-point scale) was higher than the approximately 30% diagnostic yield discussed in pretest counseling.ConclusionExome sequencing had diagnostic utility in a highly select population of fetuses where a genetic diagnosis was highly suspected. Challenges related to genetics literacy and variant interpretation must be addressed by highly tailored pre- and posttest genetic counseling.

Publicly Available Data Provide Evidence against NR1H3 R415Q Causing Multiple Sclerosis

It has recently been reported that an NR1H3 missense variant, R415Q, causes a novel familial form of multiple sclerosis (Wang et al., 2016a). This claim is at odds with publicly available data from the Exome Aggregation Consortium (ExAC; http://exac.broadinstitute.org). The allele frequency of R415Q is not significantly higher in cases (0.024%-0.049%) than in ExAC population controls (0.031%), whereas if R415Q conferred even 50% lifetime risk of developing MS, it would be hundreds of times more common in cases than in controls. The upper bound of the 95% confidence interval of penetrance for R415Q can be estimated at 2.2% for women and 1.2% for men, indicating that even if this variant is disease associated, individuals harboring the variant would have a lifetime risk of developing MS no higher than a few percent. ExAC data should be considered when evaluating claims of variant pathogenicity. This Matters Arising paper is in response to Wang et al. (2016a), published in Neuron. See also the related Matters Arising paper by The International Multiple Sclerosis Genetics Consortium (2016) and the response by Wang et al. (2016b), published in this issue.

Intersection of Proteomics and Genomics to "Solve the Unsolved" in Rare Disorders such as Neurodegenerative and Neuromuscular Diseases

Despite recent rapid advances in sequencing technologies, a significant proportion of patients with rare genetic disorders do not receive a genetic diagnosis after exhaustive testing, and even fewer have a potential therapeutic target identified. Taking rare neuromuscular and neurodegenerative disorders as a paradigm that can be extended to other rare Mendelian disorders, this viewpoint explores the opportunities that are brought about by the integration of genomics and proteomics, as well as the limitations and remaining challenges of this newly emerging field of proteogenomics. The relevance of combining proteomic findings with genetic results for diagnosis and gene discovery is illustrated, highlighting the insights the combined analysis provides into the underlying biology and aetiology as well as the limitations of the experimental techniques. A final discussion focuses on the importance of mechanisms to enable the sharing, reuse, and analysis of source experimental data and describes some of the international initiatives that are making progress in this area.

A Comparison of Whole Genome Sequencing to Multigene Panel Testing in Hypertrophic Cardiomyopathy Patients

BACKGROUND

As DNA sequencing costs decline, genetic testing options have expanded. Whole exome sequencing and whole genome sequencing (WGS) are entering clinical use, posing questions about their incremental value compared with disease-specific multigene panels that have been the cornerstone of genetic testing.

METHODS AND RESULTS

Forty-one patients with hypertrophic cardiomyopathy who had undergone targeted hypertrophic cardiomyopathy genetic testing (either multigene panel or familial variant test) were recruited into the MedSeq Project, a clinical trial of WGS. Results from panel genetic testing and WGS were compared. In 20 of 41 participants, panel genetic testing identified variants classified as pathogenic, likely pathogenic, or uncertain significance. WGS identified 19 of these 20 variants, but the variant detection algorithm missed a pathogenic 18 bp duplication in myosin binding protein C (MYBPC3) because of low coverage. In 3 individuals, WGS identified variants in genes implicated in cardiomyopathy but not included in prior panel testing: a pathogenic protein tyrosine phosphatase, non-receptor type 11 (PTPN11) variant and variants of uncertain significance in integrin-linked kinase (ILK) and filamin-C (FLNC). WGS also identified 84 secondary findings (mean=2 per person, range=0-6), which mostly defined carrier status for recessive conditions.

CONCLUSIONS

WGS detected nearly all variants identified on panel testing, provided 1 new diagnostic finding, and allowed interrogation of posited disease genes. Several variants of uncertain clinical use and numerous secondary genetic findings were also identified. Whereas panel testing and WGS provided similar diagnostic yield, WGS offers the advantage of reanalysis over time to incorporate advances in knowledge, but requires expertise in genomic interpretation to appropriately incorporate WGS into clinical care.

CLINICAL TRIAL REGISTRATION

URL: https://clinicaltrials.gov. Unique identifier: NCT01736566.

Transformative therapies for rare CFTR missense alleles

With over 1900 variants reported in the cystic fibrosis transmembrane conductance regulator (CFTR), enhanced understanding of cystic fibrosis (CF) genotype-phenotype correlation represents an important and expanding area of research. The potentiator Ivacaftor has proven an effective treatment for a subset of individuals carrying missense variants, particularly those that impact CFTR gating. Therapeutic efforts have recently focused on correcting the basic defect resulting from the common F508del variant, as well as many less frequent missense alleles. Modest enhancement of F508del-CFTR function has been achieved by combining Ivacaftor with Lumacaftor, a compound that aids maturational processing of misfolded CFTR. Continued development of in silico and in vitro models will facilitate CFTR variant characterization and drug testing, thereby elucidating heterogeneity in the molecular pathogenesis, phenotype, and modulator responsiveness of CF.

Dilated Cardiomyopathy: Genetic Determinants and Mechanisms

Nonischemic dilated cardiomyopathy (DCM) often has a genetic pathogenesis. Because of the large number of genes and alleles attributed to DCM, comprehensive genetic testing encompasses ever-increasing gene panels. Genetic diagnosis can help predict prognosis, especially with regard to arrhythmia risk for certain subtypes. Moreover, cascade genetic testing in family members can identify those who are at risk or with early stage disease, offering the opportunity for early intervention. This review will address diagnosis and management of DCM, including the role of genetic evaluation. We will also overview distinct genetic pathways linked to DCM and their pathogenetic mechanisms. Historically, cardiac morphology has been used to classify cardiomyopathy subtypes. Determining genetic variants is emerging as an additional adjunct to help further refine subtypes of DCM, especially where arrhythmia risk is increased, and ultimately contribute to clinical management.

Hypertrophic Cardiomyopathy: Genetics, Pathogenesis, Clinical Manifestations, Diagnosis, and Therapy

Hypertrophic cardiomyopathy (HCM) is a genetic disorder that is characterized by left ventricular hypertrophy unexplained by secondary causes and a nondilated left ventricle with preserved or increased ejection fraction. It is commonly asymmetrical with the most severe hypertrophy involving the basal interventricular septum. Left ventricular outflow tract obstruction is present at rest in about one third of the patients and can be provoked in another third. The histological features of HCM include myocyte hypertrophy and disarray, as well as interstitial fibrosis. The hypertrophy is also frequently associated with left ventricular diastolic dysfunction. In the majority of patients, HCM has a relatively benign course. However, HCM is also an important cause of sudden cardiac death, particularly in adolescents and young adults. Nonsustained ventricular tachycardia, syncope, a family history of sudden cardiac death, and severe cardiac hypertrophy are major risk factors for sudden cardiac death. This complication can usually be averted by implantation of a cardioverter-defibrillator in appropriate high-risk patients. Atrial fibrillation is also a common complication and is not well tolerated. Mutations in over a dozen genes encoding sarcomere-associated proteins cause HCM. MYH7 and MYBPC3, encoding β-myosin heavy chain and myosin-binding protein C, respectively, are the 2 most common genes involved, together accounting for ≈50% of the HCM families. In ≈40% of HCM patients, the causal genes remain to be identified. Mutations in genes responsible for storage diseases also cause a phenotype resembling HCM (genocopy or phenocopy). The routine applications of genetic testing and preclinical identification of family members represents an important advance. The genetic discoveries have enhanced understanding of the molecular pathogenesis of HCM and have stimulated efforts designed to identify new therapeutic agents.

Sources of discordance among germ-line variant classifications in ClinVar

PurposeClinVar is increasingly used as a resource for both genetic variant interpretation and clinical practice. However, controversies exist regarding the consistency of classifications in ClinVar, and questions remain about how best to use these data. Our study systematically examined ClinVar to identify common sources of discordance and thus inform ongoing practices.MethodsWe analyzed variants that had multiple classifications in ClinVar, excluding benign polymorphisms. Classifications were categorized by potential actionability and pathogenicity. Consensus interpretations were calculated for each variant, and the properties of the discordant outlier classifications were summarized.ResultsOur study included 74,065 classifications of 27,224 unique variants in 1,713 genes. We found that (i) concordance rates differed among clinical areas and variant types; (ii) clinical testing methods had much higher concordance than basic literature curation and research efforts; (iii) older classifications had greater discordance than newer ones; and (iv) low-penetrance variants had particularly high discordance.ConclusionRecent variant classifications from clinical testing laboratories have high overall concordance in many (but not all) clinical areas. ClinVar can be a reliable resource supporting variant interpretation, quality assessment, and clinical practice when factors uncovered in this study are taken into account. Ongoing improvements to ClinVar may make it easier to use, particularly for nonexpert users.

Phenetic Comparison of Prokaryotic Genomes Using k-mers

Bacterial genomics studies are getting more extensive and complex, requiring new ways to envision analyses. Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets.

Genetics of paediatric cardiomyopathies

PURPOSE OF REVIEW

Paediatric cardiomyopathy is a rare disease with a genetic basis. The purpose of this review is to discuss the current status of genetic findings in the paediatric cardiomyopathy population and present recent progress in utilizing this information for management and therapy.

RECENT FINDINGS

With increased clinical genetic testing, an understanding of the genetic causes of cardiomyopathy is improving and novel causes are identified at a rapid rate. Recent progress in identifying the scope of genetic variation in large population datasets has led to reassessment and refinement of our understanding of the significance of rare genetic variation. As a result, the stringency of variant interpretation has increased, at times leading to revision of previous mutation results. Transcriptome and epigenome studies are elucidating important pathways for disease progression and highlight similarities and differences in pathogenesis from adult cardiomyopathy. Therapy targeted towards the underlying cause of cardiomyopathy is emerging for a number of rare syndromes such as Pompe and Noonan syndromes, and genome editing and induced pluripotent stem cells provide promise for additional precision medicine approaches.

SUMMARY

Genetics is moving at a rapid pace in paediatric cardiomyopathy. Genetic testing is increasingly being incorporated into clinical care. Although interpretation of rare genetic variation remains challenging, the opportunity to provide management and therapy targeted towards the underlying genetic cause is beginning to be realized.

Pathogenic variants in the healthy elderly: unique ethical and practical challenges

: Genetic research into ageing, longevity and late-onset disease is becoming increasingly common. Yet, there is a paucity of knowledge related to clinical actionability and the return of pathogenic variants to otherwise healthy elderly individuals. Whether or not genetic research in the elderly should be managed differently from standard practices adapted for younger populations has not yet been defined. In this article, we provide an overview of ethical and practical challenges in preparing for a genetic study of over 14 000 healthy Australians aged 70 years or older enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) Healthy Ageing Biobank. At the time of consent, all participants in this study were free of life-threatening illness, cardiovascular disease or cognitive impairment. ASPREE is thus a cohort of healthy elderly individuals with seemingly minimal burden of genetic disease recruited without ascertainment bias. The cohort presents a unique opportunity to address the penetrance of known pathogenic variants in a population without disease symptoms; however, it also raises a number of ethical concerns regarding the interpretation and disclosure of variants with known clinical actionability. Some of the challenges include (a) how to manage the interpretation, disclosure and actioning of pathogenic variants found in otherwise healthy elderly adults without disease symptoms, (b) whether or not to disclose findings for the benefit of family members rather than elderly consented donors themselves, (c) how to manage the return of genetic findings to the elderly individuals who are now in severe cognitive decline or terminal illness, (d) how to ensure quality of information and clinical service upon disclosure of results to this demographic and (e) how to prepare for the insurance implications of disclosing genetic information under Australian law. We discuss these and other dilemmas and propose a defensible plan of management.

TRIAL REGISTRATION NUMBER

ISRCTN83772183.

Genome build information is an essential part of genomic track files

Genomic locations are represented as coordinates on a specific genome build version, but the build information is frequently missing when coordinates are provided. We show that this information is essential to correctly interpret and analyse the genomic intervals contained in genomic track files. Although not a substitute for best practices, we also provide a tool to predict the genome build version of genomic track files.